Progress in image recovery technology based on deep neural network

Jie Wang; Yiwei Shi; Lewen Liang

doi:10.1117/12.3052149

11 December 2024 Progress in image recovery technology based on deep neural network

Jie Wang, Yiwei Shi, Lewen Liang

Proceedings Volume 13445, International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2024); 134452W (2024) https://doi.org/10.1117/12.3052149
Event: International Conference on Electronics. Electrical and Information Engineering (ICEEIE 2024), 2024, Haikou, China

Abstract

This paper presents the advancements in image restoration technology using deep neural networks. This paper introduces the application of deep learning in image processing, including the development of deep neural network, the advantages of convolutional neural network in image recovery, and the challenges and future trends of deep learning in image recovery. The advancements in image restoration algorithms are explored, covering the image recovery algorithm based on sparse representation, the image recovery algorithm using the variational model (VBM), and super-resolution reconstruction techniques leveraging deep learning. Through experiment and analysis, we show the effectiveness of image restoration technology based on deep neural network and compare the performance of different algorithms in image recovery. The results show that deep learning methods have better performance in image recovery tasks.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jie Wang, Yiwei Shi, and Lewen Liang "Progress in image recovery technology based on deep neural network", Proc. SPIE 13445, International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2024), 134452W (11 December 2024); https://doi.org/10.1117/12.3052149

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